1. Document hypotheses, constructs, and expected contributions.
2. Pre-register protocols on OSF or institutional repositories.
3. Align study design with ethical review outcomes and consent forms.

Data management plan

• Store raw data in encrypted, access-controlled buckets.
• Publish anonymized derivatives with clear licensing on Zenodo.
• Version datasets and metadata using DataLad.

Analysis workflow

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# Create an isolated environment
mamba env create -f environment.yml

# Execute notebooks in a controlled order
papermill pipelines/analysis.ipynb output/analysis.ipynb -p seed 123

# Validate results
pytest tests/statistics --maxfail=1

Documentation

• Maintain a living README describing objectives, dependencies, and contacts.
• Generate API docs for custom tooling with sphinx-build.
• Provide narrative summaries in the repository wiki for non-technical audiences.

Dissemination

1. Publish preprints on arXiv and deposit supplementary code in GitHub releases.
2. Submit replication packages to the DataLog datasets hub.
3. Track citations and altmetrics through ORCID, Google Scholar, and ResearchGate.

Adopt the reproducibility checklist to ensure each milestone—data, code, documentation, and publications—meets open science expectations.